arXiv subjects

Ignacio E. Sánchez

Publications and source records attributed to Ignacio E. Sánchez.

6 recordsLinked to original sources

arXiv2026

Dark energy: the cost of function in protein evolution

The evolutionary fate of proteins is driven by both folding stability and biological function, dual constraints that often conflict, creating frustration and imposing functional costs beyond stability. These costs can be captured by a "dark energy": the difference between the evolutionary energy of protein sequences and their physical folding energy. Recent advances in deep mutational scanning, protein language models, and inverse-folding models have enabled the quantification of dark energy across the protein universe. We review the computational and experimental approaches that disentangle folding and function at scale, revealing a dark energy component and providing new insights into how biological information flows from sequence to structure to function and back to sequence.

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arXiv2025

Probing the Dark Energy in the Functional Protein Universe

We show how to localize and quantify the functional evolutionary constraints on natural proteins. The method compares the perturbations caused by local sequence variants to the energetics of the protein folding process and to the corresponding change to the apparent selection landscape of sequences over the evolutionary time scale. The difference between the physical folding free energies and the evolutionary free energies can be called a "Dark Energy". We analyse various protein sets and thereby show that Dark Energy is largely localized at functional sites, which are often energetically frustrated from the point of view of folding. Overall, we find that about 25% of the positions of the folded globular proteins display some significant Dark Energy. When a function relies on a free energy that can be thermodynamically quantified, such as a binding energy to a partner, the relationship of this physical free energy with Dark Energy can be used to define a Functional Selection Temperature. We show that selection for folding and binding functions bear similar weights in specific protein-protein interactions.

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arXiv2023

Solvent constraints for biopolymer folding and evolution in extraterrestrial environments

We propose that spontaneous folding and molecular evolution of biopolymers are two universal aspects that must concur for life to happen. These aspects are fundamentally related to the chemical composition of biopolymers and crucially depend on the solvent in which they are embedded. We show that molecular information theory and energy landscape theory allow us to explore the limits that solvents impose on biopolymer existence. We consider 54 solvents, including water, alcohols, hydrocarbons, halogenated solvents, aromatic solvents, and low molecular weight substances made up of elements abundant in the universe, which may potentially take part in alternative biochemistries. We find that along with water, there are many solvents for which the liquid regime is compatible with biopolymer folding and evolution. We present a ranking of the solvents in terms of biopolymer compatibility. Many of these solvents have been found in molecular clouds or may be expected to occur in extrasolar planets.

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arXiv2022

r/K selection of GC content in prokaryotes

The GC content of prokaryotic genomes is species-specific and takes values from 16 to 77 percent. There are currently no accepted explanations for this diversity of selection for GC content. We analyzed the known correlations between GC content, genome size and amino acid cost in thousands of prokaryotes, together with new or recently compiled data on cell shape and volume, duplication times, motility, nutrient assimilation, sporulation, defense mechanisms and Gram staining. GC content integrates well with these traits into r/K selection theory when phenotypic plasticity is considered. High GC content prokaryotes are r-strategists with cheaper descendants thanks to a lower average amino acid metabolic cost and a smaller cell volume, colonize unstable environments thanks to flagella and a bacillus form and are generalists in terms of resource opportunism and the ability to defend themselves from various hazards. Low GC content prokaryotes are K-strategists specialized for stable environments that maintain homeostasis via a high-cost outer cell membrane and endospore formation as a response to nutrient deprivation and attain a higher nutrient-to-biomass yield. The lower proteome cost of high GC content prokaryotes is driven by the association between GC-rich codons and cheaper amino acids in the genetic code, while the correlation between GC content and genome size may be partly due to a shift in the functional repertoire of genomes driven by r/K selection. In all, we show that molecular diversity in the GC content of prokaryotes and the corresponding species diversity may be a consequence of ecological r/K selection

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arXiv2022

Molecular information theory meets protein folding

We propose an application of molecular information theory to analyze the folding of single domain proteins. We analyze results from various areas of protein science, such as sequence-based potentials, reduced amino acid alphabets, backbone configurational entropy, secondary structure content, residue burial layers, and mutational studies of protein stability changes. We found that the average information contained in the sequences of evolved proteins is very close to the average information needed to specify a fold ~2.2 $\pm$ 0.3 bits/(site operation). The effective alphabet size in evolved proteins equals the effective number of conformations of a residue in the compact unfolded state at around 5. We calculated an energy-to-information conversion efficiency upon folding of around 50%, lower than the theoretical limit of 70%, but much higher than human built macroscopic machines. We propose a simple mapping between molecular information theory and energy landscape theory and explore the connections between sequence evolution, configurational entropy and the energetics of protein folding.

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arXiv2013

Detecting Repetitions and Periodicities in Proteins by Tiling the Structural Space

The notion of energy landscapes provides conceptual tools for understanding the complexities of protein folding and function. Energy Landscape Theory indicates that it is much easier to find sequences that satisfy the "Principle of Minimal Frustration" when the folded structure is symmetric (Wolynes, P. G. Symmetry and the Energy Landscapes of Biomolecules. Proc. Natl. Acad. Sci. U.S.A. 1996, 93, 14249-14255). Similarly, repeats and structural mosaics may be fundamentally related to landscapes with multiple embedded funnels. Here we present analytical tools to detect and compare structural repetitions in protein molecules. By an exhaustive analysis of the distribution of structural repeats using a robust metric we define those portions of a protein molecule that best describe the overall structure as a tessellation of basic units. The patterns produced by such tessellations provide intuitive representations of the repeating regions and their association towards higher order arrangements. We find that some protein architectures can be described as nearly periodic, while in others clear separations between repetitions exist. Since the method is independent of amino acid sequence information we can identify structural units that can be encoded by a variety of distinct amino acid sequences.

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